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Articles 301 - 330 of 754
Full-Text Articles in Science and Technology Studies
Ontology Alignment For Linked Open Data, Prateek Jain, Pascal Hitzler, Amit P. Sheth, Kunal Verma, Peter Z. Yeh
Ontology Alignment For Linked Open Data, Prateek Jain, Pascal Hitzler, Amit P. Sheth, Kunal Verma, Peter Z. Yeh
Kno.e.sis Publications
The Web of Data currently coming into existence through the Linked Open Data (LOD) effort is a major milestone in realizing the Semantic Web vision. However, the development of applications based on LOD faces difficulties due to the fact that the different LOD datasets are rather loosely connected pieces of information. In particular, links between LOD datasets are almost exclusively on the level of instances, and schema-level information is being ignored. In this paper, we therefore present a system for finding schema-level links between LOD datasets in the sense of ontology alignment. Our system, called BLOOMS, is based on the …
A Taxonomy-Based Model For Expertise Extrapolation, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar, Sheron L. Decker, Amit P. Sheth
A Taxonomy-Based Model For Expertise Extrapolation, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar, Sheron L. Decker, Amit P. Sheth
Kno.e.sis Publications
While many ExpertFinder applications succeed in finding experts, their techniques are not always designed to capture the various levels at which expertise can be expressed. Indeed, expertise can be inferred from relationships between topics and subtopics in a taxonomy. The conventional wisdom is that expertise in subtopics is also indicative of expertise in higher level topics as well. The enrichment of Expertise Profiles for finding experts can therefore be facilitated by taking domain hierarchies into account. We present a novel semantics-based model for finding experts, expertise levels and collaboration levels in a peer review context, such as composing a Program …
Faculty Success: Developing A Research And Publication Agenda, Kathleen P. King
Faculty Success: Developing A Research And Publication Agenda, Kathleen P. King
Department of Leadership, Policy, and Lifelong Learning
Anyone associated with higher education will acknowledge that tenure track faculty have to perform a fantastic balancing act. Compared to an administrative or line role in an organization, higher education faculty have tremendous autonomy and freedom. However, they face competing demands of many different (and good) opportunities, and for them the stakes are always high. Help is here! This article introduces a powerful strategy for staying on track in the research strand of this competitive journey.
Ranking Documents Semantically Using Ontological Relationships, Boanerges Aleman-Meza, I. Budak Arpinar, Mustafa V. Nural, Amit P. Sheth
Ranking Documents Semantically Using Ontological Relationships, Boanerges Aleman-Meza, I. Budak Arpinar, Mustafa V. Nural, Amit P. Sheth
Kno.e.sis Publications
Although arguable success of today’s keyword based search engines in certain information retrieval tasks, ranking search results in a meaningful way remains an open problem. In this work, the goal is to use of semantic relationships for ranking documents without relying on the existence of any specific structure in a document or links between documents. Instead, real-world entities are identified and the relevance of documents is determined using relationships that are known to exist between the entities in a populated ontology. We introduce a measure of relevance that is based on traversal and the semantics of relationships that link entities …
Pattern Space Maintenance For Data Updates And Interactive Mining, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong
Pattern Space Maintenance For Data Updates And Interactive Mining, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong
Kno.e.sis Publications
This article addresses the incremental and decremental maintenance of the frequent pattern space. We conduct an in-depth investigation on how the frequent pattern space evolves under both incremental and decremental updates. Based on the evolution analysis, a new data structure, Generator-Enumeration Tree (GE-tree), is developed to facilitate the maintenance of the frequent pattern space. With the concept of GE-tree, we propose two novel algorithms, Pattern Space Maintainer+ (PSM+) and Pattern Space Maintainer− (PSM−), for the incremental and decremental maintenance of frequent patterns. Experimental results demonstrate that the proposed algorithms, on average, outperform the representative state-of-the-art …
Cross-Market Model Adaptation With Pairwise Preference Data For Web Search Ranking, Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen
Cross-Market Model Adaptation With Pairwise Preference Data For Web Search Ranking, Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen
Kno.e.sis Publications
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibility required of a commercial web search. However, manually labeled training data (with multiple absolute grades) has become the bottleneck for training a quality ranking function, particularly for a new domain. In this paper, we explore the adaptation of machine-learned ranking models across a set of geographically diverse markets with the market-specific pairwise preference data, which can be easily obtained from clickthrough logs. We propose a novel adaptation algorithm, Pairwise-Trada, which is able to adapt ranking models that are trained …
10302 Summary - Learning Paradigms In Dynamic Environments, Barbara Hammer, Pascal Hitzler
10302 Summary - Learning Paradigms In Dynamic Environments, Barbara Hammer, Pascal Hitzler
Computer Science and Engineering Faculty Publications
The seminar centered around problems which arise in the context of machine learning in dynamic environments. Particular emphasis was put on a couple of specific questions in this context: how to represent and abstract knowledge appropriately to shape the problem of learning in a partially unknown and complex environment and how to combine statistical inference and abstract symbolic representations; how to infer from few data and how to deal with non i.i.d. data, model revision and life-long learning; how to come up with efficient strategies to control realistic environments for which exploration is costly, the dimensionality is high and data …
Trust Model For Semantic Sensor And Social Networks: A Preliminary Report, Pramod Anantharam, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
Trust Model For Semantic Sensor And Social Networks: A Preliminary Report, Pramod Anantharam, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
Trust is an amorphous concept that is becoming Increasingly important in many domains, such as P2P networks, E-commerce, social networks, and sensor networks. While we all have an intuitive notion of trust, the literature is scattered with a wide assortment of differing definitions and descriptions; often these descriptions are highly dependent on a single domain or application of interest. In addition, they often discuss orthogonal aspects of trust while continuing to use the general term “trust”. In order to make sense of the situation, we have developed an ontology of trust that integrates and relates its various aspects into a …
Sit-To-Stand Detection Using Fuzzy Clustering Techniques, Tanvi Banerjee, James M. Keller, Marjorie Skubic, Carmen Abbott
Sit-To-Stand Detection Using Fuzzy Clustering Techniques, Tanvi Banerjee, James M. Keller, Marjorie Skubic, Carmen Abbott
Kno.e.sis Publications
The ability to rise from a chair is an important parameter to assess the balance deficits of a person. In particular, this can be an indication of risk for falling in elderly persons. Our goal is automated assessment of fall risk using video data. Towards this goal, we present a simple yet effective method of detecting transition, i.e. sit-to-stand and stand-to-sit, from image frames using fuzzy clustering methods on image moments. The technique described in this paper is shown to be robust even in the presence of noise and has been tested on several data sequences using different subjects yielding …
Biomedical Ontologies For Parasite Research, Vinh Nguyen, Satya S. Sahoo, Priti Parikh, Todd Minning, Brent Weatherly, Flora Logan, Amit P. Sheth, Rick Tarleton
Biomedical Ontologies For Parasite Research, Vinh Nguyen, Satya S. Sahoo, Priti Parikh, Todd Minning, Brent Weatherly, Flora Logan, Amit P. Sheth, Rick Tarleton
Kno.e.sis Publications
Trypanosoma cruzi is a protozoan parasite that causes Chagas disease or American trypanosomiasis, which is the leading cause of death in Latin America. The primary objective of this study is to create an ontology-driven information infrastructure to support parasite researchers in identifying gene knockout, vaccination, or drug targets for T. cruzi. This involves querying across multiple datasets from diverse sources, such as proteome, pathway, internal lab data, etc. that are often represented in heterogeneous formats. To address this, a multi-ontology parasite knowledge repository (PKR) is being created with an intuitive graphical query interface called Cuebee. The PKR is underpinned by …
Cloud Based Scientific Workflow For Nmr Data Analysis, Ashwin Manjunatha, Paul E. Anderson, Satya S. Sahoo, Ajith Harshana Ranabahu, Michael L. Raymer, Amit P. Sheth
Cloud Based Scientific Workflow For Nmr Data Analysis, Ashwin Manjunatha, Paul E. Anderson, Satya S. Sahoo, Ajith Harshana Ranabahu, Michael L. Raymer, Amit P. Sheth
Kno.e.sis Publications
This work presents a service oriented scientific workflow approach to NMR-based metabolomics data analysis. We demonstrate the effectiveness of this approach by implementing several common spectral processing techniques in the cloud using a parallel map-reduce framework, Hadoop.
How To Make Linked Data More Than Data, Prateek Jain, Amit P. Sheth, Kunal Verma, Pascal Hitzler, Peter Z. Yeh
How To Make Linked Data More Than Data, Prateek Jain, Amit P. Sheth, Kunal Verma, Pascal Hitzler, Peter Z. Yeh
Kno.e.sis Publications
The LOD cloud has a potential for applicability in many AI-related tasks, such as open domain question answering, knowledge discovery, and the Semantic Web. An important prerequisite before the LOD cloud can enable these goals is allowing its users (and applications) to effectively pose queries to and retrieve answers from it. However, this prerequisite is still an open problem for the LOD cloud and has restricted it to 'merely more data.' To transform the LOD cloud from 'merely more data' to 'semantically linked data' there are plenty of open issues which should be addressed. We believe this transformation of the …
Semantically Annotated Restful Services For Large-Scale Metabolomics Data Analysis, Ashwin Manjunatha, Paul E. Anderson, Satya S. Sahoo, Ajith H. Ranabahu, Michael L. Raymer, Amit P. Sheth
Semantically Annotated Restful Services For Large-Scale Metabolomics Data Analysis, Ashwin Manjunatha, Paul E. Anderson, Satya S. Sahoo, Ajith H. Ranabahu, Michael L. Raymer, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Janus: From Workflows To Semantic Provenance And Linked Open Data, Paolo Missier, Satya S. Sahoo, Jun Zhao, Carole Goble, Amit P. Sheth
Janus: From Workflows To Semantic Provenance And Linked Open Data, Paolo Missier, Satya S. Sahoo, Jun Zhao, Carole Goble, Amit P. Sheth
Kno.e.sis Publications
Data provenance graphs are form of metadata that can be used to establish a variety of properties of data products that undergo sequences of transformations, typically specified as workflows. Their usefulness for answering user provenance queries is limited, however, unless the graphs are enhanced with domain-specific annotations. In this paper we propose a model and architecture for semantic, domain-aware provenance, and demonstrate its usefulness in answering typical user queries. Furthermore, we discuss the additional benefits and the technical implications of publishing provenance graphs as a form of Linked Data. A prototype implementation of the model is available for data produced …
Provenance Management In Parasite Research, Vinh Nguyen, Priti Parikh, Satya S. Sahoo, Amit P. Sheth
Provenance Management In Parasite Research, Vinh Nguyen, Priti Parikh, Satya S. Sahoo, Amit P. Sheth
Kno.e.sis Publications
The objective of this research is to create a semantic problem solving environment (PSE) for human parasite Trypanosoma cruzi. As a part of the PSE, we are trying to manage provenance of the experiment data as it is generated. It requires to capture the provenance which is often collected through web forms used by biologists to input the information about experiments they conduct. We have created Parasite Experiment Ontology (PEO) that represents provenance information used in the project. We have modified the back end which processes the data gathered from biologists, generates RDF triples and serializes them into the triple …
Distance-Based Measures Of Inconsistency And Incoherency For Description Logics, Yue Ma, Pascal Hitzler
Distance-Based Measures Of Inconsistency And Incoherency For Description Logics, Yue Ma, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Inconsistency and incoherency are two sorts of erroneous information in a DL ontology which have been widely discussed in ontology-based applications. For example, they have been used to detect modeling errors during ontology construction. To provide more informative metrics which can tell the differences between inconsistent ontologies and between incoherent terminologies, there has been some work on measuring inconsistency of an ontology and on measuring incoherency of a terminology. However, most of them merely focus either on measuring inconsistency or on measuring incoherency and no clear ideas of how to extend them to allow for the other. In this paper, …
Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth
Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
Trust and reputation are becoming increasingly important in diverse areas such as search, e-commerce, social media, semantic sensor networks, etc. We review past work and explore future research issues relevant to trust in social/sensor networks and interactions. We advocate a balanced, iterative approach to trust that marries both theory and practice. On the theoretical side, we investigate models of trust to analyze and specify the nature of trust and trust computation. On the practical side, we propose to uncover aspects that provide a basis for trust formation and techniques to extract trust information from concrete social/sensor networks and interactions. We …
Linked Sensor Data, Harshal Kamlesh Patni, Cory Andrew Henson, Amit P. Sheth
Linked Sensor Data, Harshal Kamlesh Patni, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
A number of government, corporate, and academic organizations are collecting enormous amounts of data provided by environmental sensors. However, this data is too often locked within organizations and underutilized by the greater community. In this paper, we present a framework to make this sensor data openly accessible by publishing it on the Linked Open Data (LOD) Cloud. This is accomplished by converting raw sensor observations to RDF and linking with other datasets on LOD. With such a framework, organizations can make large amounts of sensor data openly accessible, thus allowing greater opportunity for utilization and analysis.
Trust In Social And Sensor Networks, Pramod Anantharam, Krishnaprasad Thirunarayan, Cory Andrew Henson, Amit P. Sheth
Trust In Social And Sensor Networks, Pramod Anantharam, Krishnaprasad Thirunarayan, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
Trust can be defined as the perception of the trustor about the degree to which the trustee would satisfy an expectation about a transaction constituting risk. Trust plays a pivotal role when the risk in believing incorrect information is high. With Web 2.0 where user generated content and real time interactions dominate, the openness of data contribution may hinder the quality of information we can get.
What Goes Around Comes Around - Improving Linked Open Data Through On-Demand Model Creation, Christopher Thomas, Wenbo Wang, Pankaj Mehra, Delroy H. Cameron, Pablo N. Mendes, Amit P. Sheth
What Goes Around Comes Around - Improving Linked Open Data Through On-Demand Model Creation, Christopher Thomas, Wenbo Wang, Pankaj Mehra, Delroy H. Cameron, Pablo N. Mendes, Amit P. Sheth
Kno.e.sis Publications
Web 2.0 has changed the way we share and keep up with information. We communicate through social media platforms and make the information we exchange to a large extent publicly available. Linked Open Data (LOD) follows the same paradigm of sharing information but also makes it machine accessible. LOD provides an abundance of structured information albeit in a less formally rigorous form than would be desirable for Semantic Web applications. Nevertheless, most of the LOD assertions are community reviewed and we can rely on their accuracy to a large extent. In this work we want to follow the Web 2.0 …
Dynamic Associative Relationships On The Linked Open Data Web, Pablo N. Mendes, Pavan Kapanipathi, Delroy H. Cameron, Amit P. Sheth
Dynamic Associative Relationships On The Linked Open Data Web, Pablo N. Mendes, Pavan Kapanipathi, Delroy H. Cameron, Amit P. Sheth
Kno.e.sis Publications
We provide a definition of context based on theme, time and location, and propose a mixed retrieval/extraction model for the dynamic suggestion of trending relationships to LOD resources.
Semantics-Empowered Text Exploration For Knowledge Discovery, Delroy H. Cameron, Pablo N. Mendes, Amit P. Sheth, Victor Chan
Semantics-Empowered Text Exploration For Knowledge Discovery, Delroy H. Cameron, Pablo N. Mendes, Amit P. Sheth, Victor Chan
Kno.e.sis Publications
The interaction paradigm offered by most contemporary Web Information Systems is a search-and-sift paradigm in which users manually seek information using hyperlinked documents. This paradigm is derived from a document-centric model that gives users minimal support for scanning through high volumes of text. We present a novel information exploration paradigm based on a data-centric view of corpora, along with a prototype implementation that demonstrates the value in content-driven navigation. We leverage semantic metadata to link data in documents by exploiting named relationships between entities. We also present utilities for gathering user generated navigation trails, critical for knowledge discovery. We discuss …
Designing Successful Online Courses - Part 2, Kathleen P. King
Designing Successful Online Courses - Part 2, Kathleen P. King
Department of Leadership, Policy, and Lifelong Learning
Once again, our major goal is to provide faculty with consistent guidance through the many instructional decisions and design steps they need to pursue in this process. This process is a fantastic opportunity to craft a virtual learning space in which people can engaging in learning beyond the constraints of time and space.
Five Strategies For Successful Writing Of Reports And Essays, Kathleen P. King
Five Strategies For Successful Writing Of Reports And Essays, Kathleen P. King
Department of Leadership, Policy, and Lifelong Learning
Many people cannot get started with their literary projects because they do not know where to start. In this brief article, I share insight from years of teaching students and professionals of all ages how to prepare professional work.
Understanding Events Through Analysis Of Social Media, Amit P. Sheth, Hemant Purohit, Ashutosh Sopan Jadhav, Pavan Kapanipathi, Lu Chen
Understanding Events Through Analysis Of Social Media, Amit P. Sheth, Hemant Purohit, Ashutosh Sopan Jadhav, Pavan Kapanipathi, Lu Chen
Kno.e.sis Publications
Users are sharing vast amounts of social data through social networking platforms accessible by Web and increasingly via mobile devices. This opens an exciting opportunity to extract social perceptions as well as obtain insights relevant to events around us. We discuss the significant need and opportunity for analyzing event-centric user generated content on social networks, present some of the technical challenges and our approach to address them. This includes aggregating social data related to events of interest, along with Web resources (news, Wikipedia pages, multimedia) related to an event of interest, and supporting analysis along spatial, temporal, thematic, and sentiment …
Mobicloud - Making Clouds Reachable: A Toolkit For Easy And Efficient Development Of Customized Cloud Mobile Hybrid Applications, Ashwin Manjunatha, Ajith Harshana Ranabahu, Amit P. Sheth, Krishnaprasad Thirunarayan
Mobicloud - Making Clouds Reachable: A Toolkit For Easy And Efficient Development Of Customized Cloud Mobile Hybrid Applications, Ashwin Manjunatha, Ajith Harshana Ranabahu, Amit P. Sheth, Krishnaprasad Thirunarayan
Kno.e.sis Publications
The advancements in computing have resulted in a boom of cheap, ubiquitous, connected mobile devices, as well as seemingly unlimited, utility style, pay as you go computing resources, commonly referred to as Cloud computing. However, taking full advantage of this mobile and cloud computing landscape, especially for the data intensive domains, has been hampered by the many heterogeneities that exist in the mobile space, as well as the Cloud space. Our research attempts to exploit the capabilities of the mobile and cloud landscape by introducing MobiCloud, an online toolkit to efficiently develop Cloud-mobile hybrid (CMH) applications. We define a CMH …
Nominal Schemas For Integrating Rules And Ontologies, Frederick Maier, Adila A. Krisnadhi, Pascal Hitzler
Nominal Schemas For Integrating Rules And Ontologies, Frederick Maier, Adila A. Krisnadhi, Pascal Hitzler
Computer Science and Engineering Faculty Publications
We propose a description-logic style extension of OWL DL, which includes DL-safe variable SWRL and seamlessly integrates datalog rules. Our language also sports a tractable fragment, which we call ELP 2, covering OWL EL, OWL RL, most of OWL QL, and variable restricted datalog.
Scale: A Scalable Framework For Efficiently Clustering Transactional Data, Hua Yan, Keke Chen, Ling Liu, Zhang Yi
Scale: A Scalable Framework For Efficiently Clustering Transactional Data, Hua Yan, Keke Chen, Ling Liu, Zhang Yi
Kno.e.sis Publications
This paper presents SCALE, a fully automated transactional clustering framework. The SCALE design highlights three unique features. First, we introduce the concept of Weighted Coverage Density as a categorical similarity measure for efficient clustering of transactional datasets. The concept of weighted coverage density is intuitive and it allows the weight of each item in a cluster to be changed dynamically according to the occurrences of items. Second, we develop the weighted coverage density measure based clustering algorithm, a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Third, we introduce two clustering validation metrics and show that these domain …
From Questions To Effective Answers: On The Utility Of Knowledge-Driven Querying Systems For Life Sciences Data, Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya S. Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton
From Questions To Effective Answers: On The Utility Of Knowledge-Driven Querying Systems For Life Sciences Data, Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya S. Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton
Kno.e.sis Publications
We compare two distinct approaches for querying data in the context of the life sciences. The first approach utilizes conventional databases to store the data and intuitive form-based interfaces to facilitate easy querying of the data. These interfaces could be seen as implementing a set of 'pre-canned' queries commonly used by the life science researchers that we study. The second approach is based on semantic Web technologies and is knowledge (model) driven. It utilizes a large OWL ontology and same datasets as before but associated as RDF instances of the ontology concepts. An intuitive interface is provided that allows the …
Sensor Discovery On Linked Data, Josh Pschorr, Cory Andrew Henson, Harshal Kamlesh Patni, Amit P. Sheth
Sensor Discovery On Linked Data, Josh Pschorr, Cory Andrew Henson, Harshal Kamlesh Patni, Amit P. Sheth
Kno.e.sis Publications
There has been a drive recently to make sensor data accessible on the Web. However, because of the vast number of sensors collecting data about our environment, finding relevant sensors on the Web is a non-trivial challenge. In this paper, we present an approach to discovering sensors through a standard service interface over Linked Data. This is accomplished with a semantic sensor network middleware that includes a sensor registry on Linked Data and a sensor discovery service that extends the OGC Sensor Web Enablement. With this approach, we are able to access and discover sensors that are positioned near named-locations …